In this course, learners will build a strong foundation in data analytics – from understanding data types, quality, and statistical thinking to creating meaningful visualizations and communicating insights effectively. Learners will develop hands-on skills in Excel for data exploration, analysis, and pivot tables, and will use SQL to query, manipulate, and aggregate data across relational databases. They will master data visualization and storytelling in Tableau, building interactive dashboards and compelling visual narratives. Learners will also apply classification algorithms including K-Nearest Neighbors, Decision Trees, and Support Vector Machines, and explore unsupervised learning techniques such as clustering and Principal Component Analysis (PCA) alongside feature engineering methods.